metadata and for posts originating from different social media sources and the posts themselves may be collected. A query specifying search criteria for the posts and filter criteria related to the metadata may be submitted to the system disclosed herein. The system may allow a client or tenant of the system to filter and search the metadata stored therein. The system may provide the posts in response to the query and permit a client or tenant to rapidly switch between social media sources and corresponding metadata types.
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12. A computer-implemented method, comprising:
obtaining, for a first database, first posts from a first social media source;
obtaining, for a second database, first metadata from the first social media source;
obtaining, for the first database, second posts from a second social media source, wherein the second posts are of a different post type than the first posts;
obtaining, for the second database, second metadata from the second social media source;
assigning, for the first posts and the second posts, identification numbers;
associating the identification numbers with the first metadata and the second metadata;
receiving a request for posts that meet search criteria for one or more media sources and filter criteria that specify a subset of at least one of the first metadata or the second metadata;
retrieving, from the first database, the identification numbers of posts that meet the search criteria, the identification numbers having been assigned to the posts;
receiving, from the second database, metadata for posts that are associated with the identification numbers and that meet the filter criteria, the metadata having corresponding identification numbers, the identification numbers having been assigned to the posts; and
providing, in response to the request, the posts that meet the search criteria and the filter criteria.
24. A non-transitory computer-readable medium storing computer code including instructions for controlling a processor to cause the processor to:
obtain, for a first database, first posts from a first social media source;
obtain, for a second database, first metadata from the first social media source;
obtain, for the first database, second posts from a second social media source, wherein the second posts are of a different post type than the first posts;
obtain, for the second database, second metadata from the second social media source;
assign, for the first posts and the second posts, identification numbers;
associate the identification numbers with the first metadata and the second metadata;
receive a request for posts that meet search criteria for one or more media sources and filter criteria that specify a subset of at least one of the first metadata or the second metadata;
retrieve, from the first database, the identification numbers of posts that meet the search criteria, the identification numbers having been assigned to the posts;
receive, from the second database, metadata for posts that are associated with the identification numbers and that meet the filter criteria, the metadata having corresponding identification numbers, the identification numbers having been assigned to the posts; and
provide, in response to the request, the posts that meet the search criteria and the filter criteria.
1. A system, comprising:
a first database configured to store at least first posts and second posts;
a second database configured to store at least first metadata and second metadata; and
a processor communicatively coupled to the first database and the second database, the processor configured to:
obtain, for the first database, the first posts from a first social media source;
obtain, for the second database, the first metadata from the first social media source;
obtain, for the first database, the second posts from a second social media source, wherein the second posts are of a different post type than the first posts;
obtain, for the second database, the second metadata from the second social media source;
assign, for the first posts and the second posts, identification numbers;
associate the identification numbers with the first metadata and the second metadata;
receive a request for posts that meet search criteria for media sources and filter criteria that specify a subset of at least one of the first metadata or the second metadata;
retrieve, from the first database, the identification numbers of posts that meet the search criteria, the identification numbers having been assigned to the posts;
receive, from the second database, metadata for posts that are associated with the identification numbers and that meet the filter criteria, the metadata having corresponding identification numbers, the identification numbers having been assigned to the posts; and
provide, in response to the request, the posts that meet the search criteria and the filter criteria.
3. The system of
send, to the first database, a request for the posts that meet the search criteria; and
send, to the second database, a request for the metadata for the posts that are associated with the identification numbers and that meet the filter criteria.
4. The system of
serialize the first metadata and the second metadata; and
store the first metadata and the second metadata.
5. The system of
6. The system of
7. The system of
8. The system of
9. The system of
10. The system of
11. The system of
13. The method of
14. The method of
15. The method of
16. The method of
17. The method of
19. The method of
sending, to the first database, a request for the posts that meet the search criteria; and
sending, to the second database, a request for the metadata for the posts that are associated with the identification numbers and that meet the filter criteria.
20. The method of
serializing the first metadata and the second metadata; and
storing the first metadata and the second metadata.
21. The method of
22. The method of
23. The method of
25. The non-transitory computer-readable medium of
26. The non-transitory computer-readable medium of
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This application claims priority to provisional application No. 61/893,582 that was filed on Oct. 21, 2013 and is hereby incorporated by reference in its entirety.
Embodiments of the subject matter described herein relate generally to computer systems. More particularly, embodiments of the subject matter relate to web-based content analytics systems.
Computer based systems that analyze social media trends, user posts, and online content can be used to measure a variety of metrics. Social listening analytics techniques can be used to monitor and analyze social media activity. For example, a broad listening methodology may track various statistics, such as a current view count for content on a website, the number of replies to a user post, the number of reposts a message, or the like. The data accumulated from social media websites is voluminous and presents unique challenges to presenting it in a meaningful way to a client or user.
The accompanying drawings, which are included to provide a further understanding of the disclosed subject matter, are incorporated in and constitute a part of this specification. The drawings also illustrate implementations of the disclosed subject matter and together with the detailed description serve to explain the principles of implementations of the disclosed subject matter. No attempt is made to show structural details in more detail than may be necessary for a fundamental understanding of the disclosed subject matter and various ways in which it may be practiced.
As disclosed herein, post data and metadata associated with posts on social network sources may be stored in separate repositories. For example, one database may contain every post made by users in a social network, and a second database may contain the metadata associated with each of the posts. For example, the second database may have geographical information about the users that created the posts, the date and time of the posts, and/or other information about the author of the posts (e.g., demographic data). A user can then run searches within the posts, and filter the results of a search based upon the collected metadata. For example, a third party business may perform a key word search for a promotion the business has recently run. The business may query each of the social network posts in the first database using the key word. Posts containing the key word are returned based on the search, and can be filtered based on the metadata in the second database. For example, the business may view the posts returned in response to the query and select a metadata type (e.g., originating social network, post author location, date, time, etc.) by which to filter the returned posts. Because the posts and the metadata are maintained in separate repositories, the results may be rapidly filtered between social network sources and/or other metadata types associated with the returned posts. For example, all posts matching the initial search may be returned from the first database, and all associated metadata from the second database. A query system may present matching posts in a user interface that mirrors the data structure, i.e., allows the user to select metadata types and immediately see the resulting posts. The posts and/or the metadata also may be serialized or otherwise compressed, allowing for rapid transmission by the databases and rapid processing by the query system.
A system and method are provided that collect metadata for posts from social media sources (or media providers). Metadata may refer to data about a post rather than the content of the post itself. Examples of metadata includes, for example, a time reference, a language, an author, a geographic location, a URL, or any other information that describes the data (e.g., a post on a social media source). The posts and corresponding metadata may be filtered and searched within the system. A social media source may refer to a website on which a user may be linked or connected to other users in the form of a friend group or a “follower.” A user of a social media source may post content that can be shared to individuals within a particular group (e.g., a friend group) or publicly shared. A database may be populated with metadata and/or data for posts based on content obtained by a web crawler. The web crawlers may identify posts to be retrieved from the social media sources or other online sources by searching for a keyword match.
One or more of a user's posts, the metadata corresponding to the user's posts, posts responsive to the user's posts, metadata corresponding to the responsive posts, and/or a user's profile on the social media source, may not be readily available to the public or accessible by a web crawler. The social media source, however, may provide or otherwise make available the publicly unavailable data and/or metadata to collaborating partners. The posts and the metadata for each post may be stored in separate repositories. The data representing posts may be retrieved faster and separately in such a configuration than if the posts and the metadata were combined in a single large repository. Upon receipt of a query for posts, specific metadata specified in the query may be obtained from the repository containing the metadata. The metadata and the posts may be provided as a response to the query for display to one or more clients. Data and metadata may be ingested by the system from a variety of sources in different ways. The system, such as the example shown in
In some configurations, the client device request at 241 may include only a key word and specify a provider or social media source. After the query engine 220 has received the posts at 253, based on the post identification numbers, that match the key word provided by the request at 241, the client may submit a second request to the query engine 220 that specifies a particular type of metadata (e.g., a particular location). The query engine would submit the request at 461 subsequent to the second request from the client device 410. Subsequent to 263, the query engine 220 may generate a response that is sent to the front end application that changes the view for the client device 210 based on the response generated by the query engine 220. The response may be provided to the client device 220 at 243.
For example, if a user requested all of the social media posts from source ABC that match (e.g., include) the word “baseball,” the system may return a list of 500 million posts or an abbreviated representation thereof (e.g., a shortened list, an indication of the number of hits returned, a random or non-random selection of matching posts, etc.) if the number, as in this case, is too large to reasonably be displayed to a client device 210. If the client device 210 specifies that the posts must have occurred within the last week and be from Japan, the system may retrieve only those posts whose identification numbers were obtained from the first query (i.e., “baseball”) and further refine the returned list to those posts containing “baseball” and whose media type (e.g., geolocation and time) corresponds to Japan and that were made in the last week. The system may represent the data in a variety of ways including altering the user interface or presenting the returned results in an analytical form such as a graphical representation (e.g., a pie chart). If the client device 210 submits a new metadata filter request, such as requesting the posts from the first query (i.e., “baseball”) that were from the U.S. and made within the last 7 days, the system may again submit the third request to the query engine 220, which will obtain the appropriate posts that correspond to the specified metadata filter. The client device 110 may, therefore toggle between the different metadata filters that the user would like to apply.
The system user interface may offer the client device the ability to filter the retrieved posts that match the key word based on the social media source and/or preset metadata filters. As in the example above, a query for the word “baseball” may be offer the client device the ability to filter based on several, possibly overlapping, geographic boundaries, time, attachments (e.g., pictures, audio, video, etc.) to the posts, demographic information, social media source, etc. The system may offer premium content for some clients that may present those clients with more available filters than a non-premium client. In some instances, a first social media source and a second social media source may not have the same metadata available. In the event the client device selects or enters a metadata filter that is not available in a social media source, the posts for that social media source may not be displayed.
The system may have predefined media types for the metadata such as geolocation. However, during the data/metadata ingestion process, the system will collect any data/metadata available. The system does not need to explicitly define the collected metadata as a media type. As such, the system may accommodate new forms of metadata that may become available for existing social media sources or new social media sources.
According to an implementation, an example of which is provided in
As an example, the data may be organized by the system, and stored in one or more databases, in the following format: Post identifier (source, text, picture data, location data, time reference, user data 1, user data 2). The post identifier may be utilized to associate the data of the post with the metadata. In the event the databases that store the content are sharded, the post identifier may be utilized to recombine the data in a desired format. Although the example in
Returning to
A system is disclosed that includes a database for storing at least one of first posts, second posts, first metadata and second metadata. The database may be communicatively coupled to a processor. As described earlier, the system may include multiple databases, each of which stores post data or metadata. For example, the query engine shown in
In an implementation, an example of which is provided in
As another example, a first social media source may be a blog post and the second social media post may be a tweet. The metadata available from the first source may differ from the metadata available from the second source as well. Thus, in implementations disclosed herein, the data and metadata ingested from a variety of social media sources may differ in format and content. The system may extract features from the data and metadata before storing it in a database in order to unify the organization and/or structure of the data and metadata in some configurations. For example, a social media source may provide a specification for how post data and metadata associated therewith will be provided such as via a published API. Each social media source's published specification can be mapped to a unified database structure.
A request for posts meeting search criteria for one or more of the social media sources may be received at 450. The request may specify filter criteria at this time or subsequent to retrieval of the posts meeting the search criteria as described earlier. Result posts that meet the search criteria may be identified at 460 and final posts may be selected from those result posts that meet the filter criteria at 470. The final posts may be provided in response to the request as described earlier.
In some instances, metadata may be provided or obtained from a third party analytics provider. Analytics may refer to the measurement, collection, analysis, and reporting of data regarding, for example, a web site's usage or a popularity of a product online. For example, the analytics for a social media source may include data about the visibility or comments related to a particular product or promotion. It may include user behavior upon presentation of a product or promotion. These data may be included in the implementations disclosed above.
The system disclosed herein may be implemented as a multi-tenant system. The system may include a server that can generate one or more virtual applications based on data stored in a common database shared between the tenants. Each virtual application may provide access to data in the database for each of the one or more tenants utilizing the system. A tenant may refer to a group of users that shares access to common data within a database. A tenant may represent customers, customer departments, business or legal organizations, and/or any other entities that maintain data for particular sets of users. A tenant may, for example, request social media posts, metadata, and/or analytics provider data. Although multiple tenants may share access to a common server and database, the particular data and services provided from the system to each tenant can be securely isolated from those provided to other tenants. The multi-tenant architecture therefore allows different sets of users to share functionality without necessarily sharing each other's data. Similarly, the appearance of each tenant's interface with the system may be unique.
In some configurations, the system may receive an indication that a user has entered a particular location such as a department store. The user may be determined to be in proximity of the department store by GPS data associated with a user's smartphone or other indicators of the user's presence in the store. For example, the user may check-in at the store via a social network. The check-in may be broadcast to the user's friends via the social network. The system may associate purchases by a user at a particular department store or the like (e.g., restaurants) with the metadata stored in the database. Further the system may analyze the user's purchase habits to determine trends in the types of items a user's purchases, the stores a user frequents, and the amount of money expended per visit or per store, for example. The purchase habits, purchase history, check-in posts, etc. may be stored as metadata that can be associated with the user.
Implementations of the presently disclosed subject matter may be implemented in and used with a variety of component and network architectures.
The bus 21 allows data communication between the central processor 24 and the memory 27, which may include read-only memory (ROM) or flash memory (neither shown), and random access memory (RAM) (not shown), as previously noted. The RAM is generally the main memory into which the operating system and application programs are loaded. The ROM or flash memory can contain, among other code, the Basic Input-Output system (BIOS) which controls basic hardware operation such as the interaction with peripheral components. Applications resident with the computer 20 are generally stored on and accessed via a computer readable medium, such as a hard disk drive (e.g., fixed storage 23), an optical drive, floppy disk, or other storage medium 25.
The fixed storage 23 may be integral with the computer 20 or may be separate and accessed through other interfaces. A network interface 29 may provide a direct connection to a remote server via a telephone link, to the Internet via an internet service provider (ISP), or a direct connection to a remote server via a direct network link to the Internet via a POP (point of presence) or other technique. The network interface 29 may provide such connection using wireless techniques, including digital cellular telephone connection, Cellular Digital Packet Data (CDPD) connection, digital satellite data connection or the like. For example, the network interface 29 may allow the computer to communicate with other computers via one or more local, wide-area, or other networks, as shown in
Many other devices or components (not shown) may be connected in a similar manner (e.g., document scanners, digital cameras and so on). Conversely, all of the components shown in
More generally, various implementations of the presently disclosed subject matter may include or be implemented in the form of computer-implemented processes and apparatuses for practicing those processes. Implementations also may be implemented in the form of a computer program product having computer program code containing instructions implemented in non-transitory and/or tangible media, such as floppy diskettes, CD-ROMs, hard drives, USB (universal serial bus) drives, or any other machine readable storage medium, wherein, when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing implementations of the disclosed subject matter. Implementations also may be implemented in the form of computer program code, for example, whether stored in a storage medium, loaded into and/or executed by a computer, or transmitted over some transmission medium, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein when the computer program code is loaded into and executed by a computer, the computer becomes an apparatus for practicing implementations of the disclosed subject matter. When implemented on a general-purpose microprocessor, the computer program code segments configure the microprocessor to create specific logic circuits. In some configurations, a set of computer-readable instructions stored on a computer-readable storage medium may be implemented by a general-purpose processor, which may transform the general-purpose processor or a device containing the general-purpose processor into a special-purpose device configured to implement or carry out the instructions, Implementations may be implemented using hardware that may include a processor, such as a general purpose microprocessor and/or an Application Specific Integrated Circuit (ASIC) that implements all or part of the techniques according to implementations of the disclosed subject matter in hardware and/or firmware. The processor may be coupled to memory, such as RAM, ROM, flash memory, a hard disk or any other device capable of storing electronic information. The memory may store instructions adapted to be executed by the processor to perform the techniques according to implementations of the disclosed subject matter.
The foregoing description, for purpose of explanation, has been described with reference to specific implementations. However, the illustrative discussions above are not intended to be exhaustive or to limit implementations of the disclosed subject matter to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The implementations were chosen and described in order to explain the principles of implementations of the disclosed subject matter and their practical applications, to thereby enable others skilled in the art to utilize those implementations as well as various implementations with various modifications as may be suited to the particular use contemplated.
Luff, Michael Gordon, Hatchard, Derek Brian, Lutes, Jordan Patrick
Patent | Priority | Assignee | Title |
Patent | Priority | Assignee | Title |
8775423, | Sep 15 2011 | Verizon Argentina S.R.L. | Data mining across multiple social platforms |
8935493, | Jun 30 2011 | EMC IP HOLDING COMPANY LLC | Performing data storage optimizations across multiple data storage systems |
20120047219, | |||
20140236916, | |||
20150012593, |
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Sep 18 2014 | LUTES, JORDAN PATRICK | SALESFORCE COM, INC | ASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS | 033883 | /0810 | |
Sep 22 2014 | HATCHARD, DEREK BRIAN | SALESFORCE COM, INC | ASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS | 033883 | /0810 | |
Sep 30 2014 | LUFF, MICHAEL GORDON | SALESFORCE COM, INC | ASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS | 033883 | /0810 | |
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Mar 25 2022 | SALESFORCE COM, INC | SALESFORCE, INC | CHANGE OF NAME SEE DOCUMENT FOR DETAILS | 069268 | /0034 |
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